Elena Korkina

Intelligent Coordinated Operation and Emergency Control in Electric Power Systems

Nowadays electric power industry is undergoing radical transformations. Therefore it is necessary to enhance the efficiency of electric power system operation and emergency control. The paper presents the main features of the advanced system for monitoring and forecasting of operating conditions and control of electric power systems. Current state estimation through the integration of traditional information and artificial intelligence technologies is presented. Short-term forecasting of operating conditions by advanced information technologies is discussed. The technique for adaptation of fuzzy logic PSS is suggested. Coordinated emergency control of load and FACTS devices is studied. PMU application to control transients by FACTS devices is discussed.

Monitoring of EPS operation by the state estimation methods

State estimation is the most important procedure providing the electric power system control with reliable quality information. The role of state estimation problem is getting more pronounced with transition to a qualitatively new level of technologies and control of power systems based on the wide-area monitoring and control systems (WAMS/WACS). Currently the electric power system (EPS) state estimation methods are developed on the basis of combined application of conventional measurements from SCADA and phasor measurement that are provided by PMU. Practical application of PMUs reveals a number of factors that affect the correctness of their measurements. Therefore, the need arises to verify the PMU measurements. The paper suggests the approaches to validation of PMU measurements on the basis of test equation technique. Consideration is given to the modification of state estimation algorithm by combining the SCADA and PMU measurements.

Smart Technologies in Emergency Control of Russia's Unified Energy System

The objective trends in electric power systems (EPSs) call for prompter and more adequate response of control systems. New smart measurement, communication and control tools, information and computer technologies can be used to improve EPS controllability. The distinctive features of the Unified Energy System (UES) of Russia are discussed and the current emergency control system is presented in the paper. A modern approach to monitoring, forecasting and control is suggested. Some artificial intelligence applications for development of emergency control in the UES of Russia are presented.

The test equation method for linear state estimation based on PMU data

The advent of next generation devices for synchronized phasor measurements (voltage and current values in lines) - PMU - makes it possible to realize linear algorithms of state estimation. The paper suggests the development of the test equation technique for linear state estimation of power system facilities that are monitored on the basis of PMU measurements. New algorithms for the construction of the test equations on the basis of PMU measurements are presented. The algorithms are based on the exclusion of unmeasured variables or state vector components from the electrical circuit equations written in the rectangular coordinates. By virtue of linear nature of these equations the obtained test equations are also linear. The paper presents the algorithms for bad data detection in PMU measurements as well as the algorithms for calculation of estimates, using linear test equations which make it possible to obtain a solution within one iteration. Performance of the algorithms was tested on a test network equipped with PMUs. The developed algorithms allow us to make local state estimation of individual power system facilities (power plants, substations, network sections) that are monitored online on the basis of PMU measurements.

Intelligent control and protection in the Russian electric power system

Abstract The chapter presents the following contributions: (1) a general overview of an intelligent electric power system with an active and adaptive network (IESAAN) as the Russian vision of a smart grid, its technological platform, and control system; (2) state estimation (SE) techniques as informational support of the IESAAN control including SE with phasor measurements use, FACTS modeling in SE applications, dynamic SE, and cyber-physical security issues of SE; (3) intelligent operation and smart emergency protection in Russia including requirements for new protection systems; a novel system of monitoring, forecasting, and control of electric power system (EPS); artificial intelligence applications in EPS such as a forecast of state variables based on dynamic SE and hybrid data-driven approaches; a total transfer capability estimation method; an automatic decision tree-based system for online voltage security control; a multiagent coordination of emergency control devices; and an intelligent system for preventing large-scale emergencies; (4) a description of smart grid territorial clusters in the interconnected power systems of Russia.

PMU Placement Based on Heuristic Methods, when Solving the Problem of EPS State Estimation

Creation of satellite communication systems gave rise to a new generation of measurement equipment – Phasor Measurement Unit (PMU). Integrated into the measurement system WAMS, the PMU sensors provide a real picture of state of energy power system (EPS). The issues of PMU placement when solving the problem of EPS state estimation (SE) are discussed in many papers. PMU placement is a complex combinatorial problem, and there is not any analytical function to optimize its variables. Therefore, this problem is often solved by the heuristic optimization methods. Depending on the chosen set of sensors (SCADAP only PMU; PMU placement based on the concept of depth of unobservability), one can obtain no less than 3 different variants of placing PMUs for one and the same system. The paper describes the PMU placement criteria suggested by the authors to solve the SE problem. Among them: improvement of bad data detection, maximum accuracy of estimates, transformation of the system graph into a tree, maximum number of measurements to be added, PMU placement during the decomposition of the power system SE problem. It is shown that the correct selection of PMU placement criteria can improve the solutions to these problems.

Distributed State Estimation

The previous chapter focused on Wide Area Measurement Systems, that are typically used to oscillations within the transmission systems by comparing time synchronized measurements of different locations. By contrast, this and the following two chapters focus on the use of modern monitoring technologies (compare Chap. 4) for static observation of large scale transmission systems with State Estimation (SE) tools. SE was firstly introduced in the 1970s to improve monitoring of Electric Power Systems (EPS). SE is an important procedure that allows for on-line calculation of state variables for a current situation of the EPS on the basis of measured state variables and signals about the switching state of power system equipment. The obtained SE model of the power system is then used in control centers for observation and control of the EPS.